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AlexMaclean/sentence-compression

sourceHugging Faceapache-2.0updated 5y agoView on Hugging Face
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Model Card

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sentence-compression

This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2973
  • Accuracy: 0.8912
  • F1: 0.8367
  • Precision: 0.8495
  • Recall: 0.8243

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • trainbatchsize: 16
  • evalbatchsize: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 500
  • num_epochs: 3

Training results

Training LossEpochStepValidation LossAccuracyF1PrecisionRecall
0.26861.0100000.26670.88940.82830.87250.7884
0.22052.0200000.27040.89250.83720.85790.8175
0.14763.0300000.29730.89120.83670.84950.8243

Framework versions

  • Transformers 4.12.5
  • Pytorch 1.10.0+cu113
  • Datasets 1.16.1
  • Tokenizers 0.10.3